Large scale positioning systems that track thousands of devices and leverage hundreds of Access Points (“AP”) have become an extremely critical component of real world wireless deployments. Customer engagement, asset tracking and indoor navigation are some concrete applications that can leverage indoor positioning systems. These positioning systems may use angle-of-arrival (“AoA”) and/or received signal strength indication (“RSSI”) measurements to achieve a location accuracy to within one to three meters, each location computation is typically expensive. Inertial sensor data, conventionally used to detect motion of user computing devices, is typically not available to location determination systems. As users are often stationary for a considerable amount of time in enterprise setups (workplaces, hospitals, etc.), positioning systems unnecessarily recompute location computations. As such, existing indoor positioning systems have provided considerable accuracy, but limited scalability and coverage
Current applications for determining user computing device position do not provide for efficient positioning based on movement classification.